Magnetic Resonance Imaging (MRI) is a non-invasive medical imaging technique that utilizes magnetization to visualize soft tissue. Echo Planar Imaging (EPI) is a widely used method for rapidly acquiring MRI images. EPI may be used, for example, for measuring dynamic activity in the brain with functional MRI and for increasing the time efficiency in diffusion-weighted or perfusion-weighted MRI. Ideally, each EPI slice is acquired in a single shot to minimize its vulnerability to tissue or organ motion. However, in some cases, single-shot acquisitions are infeasible because of the long encoding trains required. As the image encoding time (i.e., the full image readout time) becomes longer, the resulting images suffer from T2* related blurring effects and B0 inhomogeneity related geometric distortion.
Accelerated parallel imaging techniques can be applied to EPI acquisitions to reduce the number of phase encoding steps and therefore reduce the total readout time. In turn, this time reduction decreases the image blur and geometric distortion artifacts caused by off-resonance effects. However, by reducing the number of phase encoding steps, accelerated techniques suffer from an inherent loss in signal-to-noise ratio (SNR) since less data is collected during the image acquisition. This missing data may be estimated using parallel imaging reconstruction techniques, but this introduces an additional loss that is dependent on the geometry and layout of the receive coil array used to detect the MR signal. The additional loss is captured quantitatively as the so-called geometry factor or “g-factor” map. This g-factor increases exponentially with the degree of acceleration. Furthermore, for a given receive coil array, there is a limit on how much an acquisition can be accelerated before the parallel imaging reconstruction is unable to remove the image undersampling artifacts introduced by the acceleration. Therefore, both the increased SNR losses and the increased image artifact levels that arise from higher acceleration factors place an upper bound on how much acceleration can be used to counter the image blur and geometric distortion seen in single-shot EPI images.
Another approach to reduce the total readout time and echo spacing is to partition each image into multiple subsets or segments and acquire each segment separately, each in a shorter time period. After acquisition, the multiple segments are assembled into a fully-sampled image. This approach reduces the readout time per segment and thus reduces the blurring effects and geometric distortion. This segmented, multi-shot approach does not suffer from the same inherent SNR loss seen in accelerated imaging because the full image is acquired, albeit in multiple steps. In conventional segmented, multi-shot imaging with multiple image slices, the first segment is acquired for each slice initially, then the second segment for each slice, and so on. This sampling strategy allows for magnetization recovery for any given image slice during the time period during which the other slices are acquired, which provides a high signal level for each image. However, this segmented multiple-slice acquisition strategy (henceforth referred to as “consecutive-slice” imaging) makes the segmented images vulnerable to artifacts caused by patient movement or by physiological changes in the tissue (e.g., caused by dynamic respiratory- or cardiac-induced effects) occurring in the interval that elapses between the acquisition of each segment in a single image. Any changes that occur between the segments result in a misalignment of the data acquired across the segments and cause severe image artifacts in the assembled image. Furthermore, while each individual segment is acquired in a short time window in order to reduce blurring effects and geometric distortion, the total time to acquire a full image is increased as the number of segments increases, leading to a loss of temporal efficiency which can prolong scan times. Thus, the prolonged scan time places an upper bound on how much segmentation can be used to counter the image blur and geometric distortion seen in un-accelerated EPI images.
Accordingly, it is desired to provide segmented acquisition strategy that is less vulnerable than the aforementioned consecutive-slice imaging to image blur, geometric distortion, and other artifacts caused by patient movement or by physiological changes in the tissue.